Many of the bearer services that will be available over 3 G (Third Generation) Wireless Systems such as UMTS (universal mobile telecommunications system) use block-based transmissions that, although protected by a Cyclic Redundancy Check (CRC), possess long transmission time intervals (TTI) that make necessary the estimation of bit error probability within the block and before the CRC is checked. As such, to provide some limited error protection these bearer services can employ convolutional or turbo encoding. In addition, these services typically require provisioning a certain Quality of Service (QoS) that is specified in terms of the average Bit-Error-Rate (BER) as seen by the end user. To that end, a wireless receiver needs to provide a BER estimate from the convolutional or turbo encoded received signal to support these services and their ability to deliver the desired QoS to the end user.
For bearer services employing turbo encoding, it is known in the art that a receiver can provide BER estimates for a received signal by using iterative decoding methods based on Maximum Aposteriori Probability (MAP) decoders or variants thereof (such as log-MAP, or Soft Output Viterbi Algorithm (SOVA)). These methods produce soft outputs representing the aposteriori log likelihood ratios for the received bits. From these soft outputs, BER estimates are computed in a straightforward manner.
In contrast, for those bearer services employing a convolutional coding scheme, there is a need to provide a method and apparatus to estimate the bit error rate—and, therefore, provide the ability to estimate the QoS as seen by the end user.